Murphy AI is a next-generation debt collection platform powered by artificial intelligence , designed to optimize recovery rates while maintaining respectful and personalized communication. Our advanced automation streamlines the process of collecting overdue invoices for businesses, providing a seamless and effective solution .
At Murphy AI, we’re tackling one of the toughest challenges in fintech : making debt recovery more efficient, autonomous and scalable. Our AI-powered agents adapt instantly, engaging with debtors across channels like voice, email and sms to maximize results while preserving trust. By combining advanced artificial intelligence with powerful automation, we’re setting a new standard for how businesses recover payments .
As a fast-growing startup that has already made an impact within less than a year in the market, we are building a talented team to scale our operations and drive our vision forward
About the Role
We’re looking for a Senior Technical Product Manager to translate the product vision and strategy into outstanding execution across our platform. This role requires someone with a strong technical and analytical foundation, proven ability to simplify complexity, and a relentless focus on measurable business impact.
You’ll take ownership of the end-to-end product lifecycle, from user research and discovery through delivery and iteration, while collaborating closely with engineering, data, and operations. Most importantly, you’ll help us design a platform that scales, creates real client value, and sets the foundation for Murphy’s long-term growth.
Responsibilities
1. Technical & Analytical Excellence (Must-have)
- Design and manage backend-heavy, configurable, and scalable platforms.
- Understand architectures, APIs, data models, and complex business logic.
- Engage with AI / ML-driven features : configuring prompts, events, detections, and modular components.
2. Product Strategy & Platform Vision
Define platform vision beyond features—systems, frameworks, and reusable configurations.Balance short-term business needs with long-term technical health, managing technical debt pragmatically.Improve operational workflows and automation, ensuring orchestration and reporting are scalable.3. Hands-on Execution & Delivery
Own the full product lifecycle : discovery, user stories, prioritization, sprint execution, QA, launch, and post-launch analysis.Operate autonomously in ambiguous environments, proactively spotting gaps and aligning stakeholders.Deliver MVPs and iterate quickly, simplifying complex challenges into clear product value.4. Data-Driven & Business Impact
Make decisions grounded in data, experimentation, and KPI analysis.Focus on measurable outcomes such as automation, improved success rates, or better customer experience.5. Collaboration & Stakeholder Management
Work cross-functionally with engineering, data, ops, and clients to deliver on commitments.Translate business needs into technical requirements and influence product decisions.Act as a constructive challenger, pushing for continuous improvement while fostering team spirit.6. Customer & User Centricity
Deeply understand client contexts, needs, and business models.Advocate for the user—whether debtor, operator, or client—and prioritize what drives real impact.Build long-term trust with enterprise customers through empathy and value creation.Requirements
4 years proven experience in backend-heavy, data-driven, or AI / ML-enabled products.Track record of shipping products from scratch or in high-growth environments.Strong analytical mindset with ability to interpret product KPIs and experiment effectively.Excellent communication, documentation, and stakeholder management skills.Fluent English (written and spoken).Comfortable operating in a fast-paced, evolving startup environment.Degree in engineering, computer science, mathematics, physics, or equivalent experience with technical platforms.⭐ Bonus points if you have :
Experience in enterprise or regulated industries.Background in automation and workflow design.Proven ability to manage technical debt and scalability challenges.